Oldewage, E.T. (Elre)Engelbrecht, Andries P.Cleghorn, Christopher Wesley2018-11-282018-10Oldewage E.T., Engelbrecht A.P., Cleghorn C.W. (2018) Boundary Constraint Handling Techniques for Particle Swarm Optimization in High Dimensional Problem Spaces. In: Dorigo M., Birattari M., Blum C., Christensen A., Reina A., Trianni V. (eds) Swarm Intelligence. ANTS 2018. Lecture Notes in Computer Science, vol 11172. Springer, Cham.0302-9743 (print)1611-3349 (online)10.1007/978-3-030-00533-7_27http://hdl.handle.net/2263/67360This paper investigates the use of boundary constraint handling mechanisms to prevent unwanted particle roaming behaviour in high dimensional spaces. The paper tests a range of strategies on a benchmark for large scale optimization. The empirical analysis shows that the hyperbolic strategy, which scales down a particle’s velocity as it approaches the boundary, performs statistically significantly better than the other methods considered in terms of the best objective function value achieved. The hyperbolic strategy directly addresses the velocity explosion, thereby preventing unwanted roaming.en© Springer Nature Switzerland AG 2018. The original publication is available at : http://link.springer.combookseries/558.Particle swarm optimization (PSO)Swarm intelligenceA-particlesBoundary constraintsEmpirical analysisHigh dimensional spacesHigh-dimensional problemsLarge-scale optimizationObjective function valuesPaper testsHyperbolic functionsPostprint Article